Service des Maladies de l'Appareil Digestif, Hôpital Huriez, Lille, France; Unité INSERM U995, Lille, France.
Unité de Biostatistiques, CHRU, Lille, France.
Gastroenterology. 2015 Aug;149(2):398-406.e8; quiz e16-7. doi: 10.1053/j.gastro.2015.04.044. Epub 2015 Apr 29.
BACKGROUND & AIMS: Several models have been used to determine prognoses of patients with alcoholic hepatitis. These include static systems (the Maddrey discriminant function; age, bilirubin, international normalized ratio, creatinine [ABIC] score; and model for end-stage liver disease [MELD] score) and dynamic models (the Lille model). We aimed to combine features of all of these models to develop a better method to predict outcomes of patients with alcoholic hepatitis.
We collected data from several databases of patients with severe alcoholic hepatitis treated with corticosteroids in France and the United Kingdom to create a model to predict patient survival (derivation cohort, n = 538 patients). We compared the performances of 3 joint-effect models (Maddrey+Lille, MELD+Lille, and ABIC+Lille) to determine which combination had the best prognostic value, based on known patient outcomes. The model was validated using data from trials of the effects of corticosteroids in patients in the United States, France, Korea, and Belgium (n = 604 patients).
We created a joint-effect model to predict patient survival after 2 and 6 months; in the derivation and validation cohorts it predicted outcome significantly better than either static or dynamic models alone (P < .01 for all comparisons). The joint model accurately predicted patient survival regardless of patient risk level. The MELD+Lille combination was better than the Maddrey+Lille or ABIC+Lille combination in predicting patient survival, with Akaike information criterion values of 1305, 1313, and 1312, respectively. For example, based on the MELD+Lille combination model, the predicted 6-month mortality of complete responders with MELD scores of 15-45 (Lille score, 0.16) was 8.5% to 49.7%, compared with 16.4%-75.2% for nonresponders (Lille score, 0.45). According to the joint-effect model, for 2 patients with the same baseline MELD score of 21, the patient with a Lille score of 0.45 had a 1.9-fold higher risk of death than the patient with a Lille score of 0.16 (23.7% vs 12.5%).
By combining results from static and dynamic scoring systems for liver disease, we can better predict outcomes of patients with alcoholic hepatitis, compared with either model alone. This may help patient management and design of clinical trials.
有几种模型被用于确定酒精性肝炎患者的预后。这些模型包括静态系统(Maddrey 判别函数;年龄、胆红素、国际标准化比值、肌酐[ABIC]评分;终末期肝病模型[MELD]评分)和动态模型(利尔模型)。我们旨在结合所有这些模型的特征,开发一种更好的方法来预测酒精性肝炎患者的结局。
我们从法国和英国的几个数据库中收集了接受皮质类固醇治疗的严重酒精性肝炎患者的数据,以创建一个预测患者生存的模型(推导队列,n=538 例患者)。我们比较了 3 种联合效应模型(Maddrey+Lille、MELD+Lille 和 ABIC+Lille)的性能,以确定哪种组合具有最佳的预后价值,其依据是已知的患者结局。该模型还使用来自美国、法国、韩国和比利时的皮质类固醇治疗患者的试验数据进行了验证(n=604 例患者)。
我们创建了一个联合效应模型来预测 2 个月和 6 个月后的患者生存情况;在推导和验证队列中,它比单独的静态或动态模型都能更好地预测结局(所有比较的 P<.01)。该联合模型能够准确预测患者的生存情况,无论患者的风险水平如何。MELD+Lille 组合在预测患者生存方面优于 Maddrey+Lille 或 ABIC+Lille 组合,其 Akaike 信息准则值分别为 1305、1313 和 1312。例如,根据 MELD+Lille 组合模型,MELD 评分 15-45 分(Lille 评分 0.16)且完全应答者的 6 个月死亡率预计为 8.5%至 49.7%,而无应答者(Lille 评分 0.45)的死亡率预计为 16.4%至 75.2%。根据联合效应模型,对于基线 MELD 评分相同(21 分)的 2 例患者,Lille 评分 0.45 的患者死亡风险比 Lille 评分 0.16 的患者高 1.9 倍(23.7%比 12.5%)。
通过结合静态和动态肝病评分系统的结果,我们可以比单独使用任何一种模型更好地预测酒精性肝炎患者的结局。这可能有助于患者管理和临床试验设计。